How can China build its own silicon valley? It is the ultimate target of this research project to deal with. In order to realize this target, the research project has to solve a series of theoretical problems. Many studies reveal the reasons why Silicon Valley cannot be easily reproduced. The constantly emergency of new industry derives from the fact that the innovation cluster provides necessary mechanism to the interaction and derivation of innovative enterprises and advanced technology, and this situation forms the regional innovative knowledge ecology in the end. Knowledge is reproduced to form new knowledge in the process of flow and interaction instead of being consumed. This kind of cyclic process is innovation cluster derivation. In other words, innovation cluster has a development track which features the strong vitality, obvious sustainability, diversity and creativity. Therefore, this research needs to answer the following theoretical question: 1) Is the derivation effect the important distinctive feature of traditional industrial cluster and innovation cluster? 2) What are the main content, the influence factors and inherent law included in the innovation cluster derivation process? 3) How to take use of innovation cluster derivation to form intricate knowledge resource sharing mode and diversified technology innovation track, and even make the regional innovation system become the cradle of new industry and economic growth pole? 4) What are the modes and paths of Chinese innovation cluster considering the particularity of Chinese context? Comparing with the exist studies, this research project will manifest its characteristic in the following aspects: 1) Building up the causal relationship among knowledge interaction property, network innovation model and innovation cluster derivation, and explores a new theoretical space to observe the sustainability, diversity and creativity of the innovation cluster's development process. 2) Further subdividing the knowledge spillover effect into unconscious knowledge spillover and conscious knowledge, and distinguishing cooperative innovation into statical knowledge acquisition and dynamic knowledge creation. 3) In terms of the dynamics of innovation cluster derivation which based on innovation network cooperation, We investigate the characteristics both from the single hierarchy innovation network and cross-hierarchy innovation network. As present studies tend to ignore the interaction relationship among the different level's innovation cluster derivation driving factors, this research can cover this shortage. 4) Taking industrial differences and regional economy as two important contextual variables to explore the path of localization and globalization of innovation clusters from the perspective of global industrial chain. This innovation will cover the shortage in analyzing the innovation cluster derivation models and basic paths which specific to Chinese context.
创新集群通过创新网络有效地融合产业链、价值链和知识链,成为创新驱动型经济更为有效的产业组织载体。然而,现有研究却一直未能从理论和实证上回答这样一个问题:创新集群生生不息的成长和创新动力因何而来?更近一步即创新驱动型经济如何由创新集群衍生而来?问题进一步分解为:(1)创新网络如何使原本稀缺的知识资源越用越多?(2)创新集群衍生的知识属性特征与跨层次衍生机制是什么?(3)中国情境的创新集群衍生模式与路径是什么?本研究将通过网络分析、多层次线性模型、创新集群衍生测量等,以"创新型产业集群"为样本进行系统的回答。本研究的创新和理论特色表现为:(1)考察创新网络的特性对创新集群衍生的影响,以及有意识的知识溢出、知识创造对创新集群衍生的中介效应;(2)考察了企业创新、产业创新和区域创新的差异性,以及不同层面创新网络特征对创新集群衍生的调节机制;(3)考察中国情境下创新集群衍生模式和本地化与国际化路径。
产业集群通过内部创新型企业和高新技术的不断衍生和交互衍生,实现跨产业链生产技术间的渗透和再创新,为集权企业提供了持续的创新动力和区域创新知识生态。中国政府先后发布多条政策,开展创新型产业集群试点,以期抓住第三次工业革命的机遇,推动由创新驱动引领的经济由量到质的转型升级。因此,本研究的核心目标是回答“创新驱动型经济如何由创新集群衍生而来?”这一问题。并从以下四个方面进行回答:(1)创新网络中有意识的知识溢出与知识创造;(2)创新集群衍生的内涵、度量与基于知识资源观的实现机制;(3)多层次组织间创新网络特性与创新集群衍生动力;(4)中国创新集群衍生发展的本地化与全球化路径。并通过这四个方面的研究,形成解决现实中产业集群发展问题的科学依据,对政策制定、企业和政府的管理活动等都具有重要的启示作用。在具体的研究中,本课题采用回归模型、门槛效应模型、构建规模阈值量表等数量方法,收集“北方大企业为核心”的产业集群数据,开展定量实证研究,并从企业、产业和区域层面开展跨层次的案例研究。研究已发表学术论著18篇,其中基金委规定的重要期刊10篇,SSCI外文期刊1篇,已经撰写完成尚在审稿程序中的论文5篇。这一系列论文均针对研究的核心问题,并根据子课题的研究任务在以下四个方面集中获得成果:(1)对“创新集群”和“有意识的知识溢出”重新解释和界定,并考察了企业家导向水平对有意识的知识溢出和知识资本之间的关系;(2)探索了创新集群衍生的内涵和度量,并考察了知识创造在有意识的知识溢出和企业衍生之间的中介效应;(3)跨层次研究部分,已经撰写创新集群衍生的企业层面到产业层面,以及区域层面到产业层面创新要素的跨层次调节效应研究;(4)探究了在中国情境下,产业集群对知识溢出的诱因、知识属性与溢出渠道的匹配关系、知识溢出活跃现象的影响因素以及溢出效应的多层次考察等系列焦点议题。
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数据更新时间:2023-05-31
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